Evidence map›Paper›PMID 35401140›Full record

ArticleFrontiers in neurorobotics2022

A Compliant Force Control Scheme for Industrial Robot Interactive Operation.

Xianfa Xue, Haohui Huang, Lei Zuo, Ning Wang

Abstract read
In one paragraph

Article in Frontiers in neurorobotics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Xianfa XueKey Laboratory of Autonomous Systems and Networked Control, School of Automation Science and Engineering, South China University of Technology, Guangzhou, China.
Haohui HuangDepartment of Automation, Shanghai Jiao Tong University, Shanghai, China.
Lei ZuoSchool of Electronic and Control Engineering, Chang'an University, Xi'an, China.
Ning WangBristol Robotics Laboratory, The University of the West of England, Bristol, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To meet the enormous demand for smart manufacturing, industrial robots are playing an increasingly important role. For industrial operations such as grinding 3C products, numerous demands are placed on the compliant interaction ability of industrial robots to interact in a compliant manner. In this article, an adaptive compliant control framework for robot interaction is proposed. The reference trajectory is obtained by single-point demonstration and DMP generalization. The adaptive feedforward and impedance force controller is derived in terms of position errors, and they are input into an admittance controller to obtain the updated amount of position deviation. The compliant interaction effect is achieved, which is shown that the grinding head fits on the curved surface of a computer mouse, and the interaction force is within a certain expected range in the grinding experiment based on the performance an Elite robot. A comparative experiment was conducted to demonstrate the effectiveness of the proposed framework in a more intuitive way.

Indexed as

adaptive compliant control frameworkDMP generalizationgrinding experimentsposition deviationsingle point demonstration

Identifiers

PMID35401140
PMCPMC8984268

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.